{"id":"W4379208409","doi":"10.1101/2023.06.01.543292","title":"Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Structural Genomics Consortium; Montreal Neurological Institute and Hospital","funders":"National Institute on Aging; Genentech; Canadian Institutes of Health Research; Innovative Medicines Initiative; Mitacs; Motor Neurone Disease Association; Ontario Genomics Institute; Government of Canada; Merck KGaA; Ontario Genomics; Genome Canada; Medical Research Council; Bayer; ALS Society of Canada; McGill University; European Federation of Pharmaceutical Industries and Associations; Emory University; Bristol-Myers Squibb; Pfizer; ALS Association; Michael J. Fox Foundation for Parkinson's Research","keywords":"Antibody; Polyclonal antibodies; Proteome; Monoclonal antibody; Antibody Repertoire; Computational biology; Computer science; Biology; Immunology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002911156,0.000344445,0.0007676259,0.001381207,0.0001716203,0.00006076622,0.0005845142,0.0004855977,0.00002511182],"category_scores_gemma":[0.0004558441,0.0003403327,0.0001307452,0.002018008,0.0003830401,0.0002014892,0.0004036473,0.001140644,0.00004808191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162371,"about_ca_system_score_gemma":0.001230899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004369855,"about_ca_topic_score_gemma":0.000008499707,"domain_scores_codex":[0.9958838,0.0002700271,0.001055442,0.0009508405,0.001223372,0.0006164865],"domain_scores_gemma":[0.9958657,0.0002334638,0.0004614965,0.001266778,0.001941235,0.0002313161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002384012,0.0005878803,0.1322087,0.006879708,0.00008120212,0.00001277795,0.00003137743,0.0002229893,0.8589104,0.0007955158,0.00001723482,0.00001380096],"study_design_scores_gemma":[0.0003855561,0.0001423791,0.4595303,0.001600995,0.00004602571,5.285941e-8,0.00002166414,0.003341353,0.5343226,0.000008445862,0.0003795659,0.0002210641],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957814,0.0006375534,0.0005806287,0.0003423259,0.0001305388,0.00213729,0.0002537461,0.000115386,0.0000210928],"genre_scores_gemma":[0.9945003,0.001754618,0.00287538,0.00001040981,0.0002832769,0.0003973099,0.0000362361,0.0001039066,0.00003859117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3273216,"threshold_uncertainty_score":0.9999049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06939039209198877,"score_gpt":0.3688292214780076,"score_spread":0.2994388293860188,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}